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Policy Learning

2068 directly classified papers

Papers per year

Papers

Policy Gradient Bayesian Robust Optimization for Imitation Learning ICML 2021
The Emergence of Individuality ICML 2021
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs ICML 2021
Revisiting Peng’s Q($λ$) for Modern Reinforcement Learning ICML 2021
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021
Inverse Constrained Reinforcement Learning ICML 2021
Replay-Guided Adversarial Environment Design NIPS 2021
How Helpful is Inverse Reinforcement Learning for Table-to-Text Generation? IJCNLP 2021
Toward the Fundamental Limits of Imitation Learning NIPS 2020
Reinforcement Learning for Control with Multiple Frequencies NIPS 2020
An operator view of policy gradient methods NIPS 2020
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020
Goal-directed Generation of Discrete Structures with Conditional Generative Models NIPS 2020
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization NIPS 2020
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization NIPS 2020
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret NIPS 2020
Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel Codes NIPS 2020
Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation ICML 2020
Model-Based Reinforcement Learning with Value-Targeted Regression ICML 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning ICML 2020
Munchausen Reinforcement Learning NIPS 2020
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards NIPS 2020
Variational Policy Gradient Method for Reinforcement Learning with General Utilities NIPS 2020
Ready Policy One: World Building Through Active Learning ICML 2020
Efficient Policy Learning from Surrogate-Loss Classification Reductions ICML 2020